KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Correction for Misrecognition of Korean Texts in Signboard Images using Improved Levenshtein Metric

  • Lee, Myung-Hun (Media Service Group, Konan Technology Co. LTD.) ;
  • Kim, Soo-Hyung (Department of Computer Science, Chonnam National University) ;
  • Lee, Guee-Sang (Department of Computer Science, Chonnam National University) ;
  • Kim, Sun-Hee (Department of Computer Science, Carnegie Mellon University) ;
  • Yang, Hyung-Jeong (Department of Computer Science, Chonnam National University)
  • Received : 2011.09.05
  • Accepted : 2011.12.15
  • Published : 2012.02.28
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Abstract

Recently various studies on various applications using images taken by mobile phone cameras have been actively conducted. This study proposes a correction method for misrecognition of Korean Texts in signboard images using improved Levenshtein metric. The proposed method calculates distances of five recognized candidates and detects the best match texts from signboard text database. For verifying the efficiency of the proposed method, a database dictionary is built using 1.3 million words of nationwide signboard through removing duplicated words. We compared the proposed method to Levenshtein Metric which is one of representative text string comparison algorithms. As a result, the proposed method based on improved Levenshtein metric represents an improvement in recognition rates 31.5% on average compared to that of conventional methods.

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References

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